Multidimensional data analysis involves examining data that has multiple variables or dimensions. This approach allows researchers to explore complex relationships and patterns within the data, making it easier to understand how different factors interact. For example, a dataset might include information on age, income, and education level, enabling analysts to identify trends and correlations among these variables. Techniques used in multidimensional data analysis include data visualization, statistical modeling, and machine learning. These methods help in summarizing large datasets and extracting meaningful insights, which can be applied in various fields such as marketing, healthcare, and social sciences.